Data Science Course in Jaipur

Python basics: syntax, variables, data types, conditionals, loops

Functions, error handling, and object-oriented programming (OOP)

Jupyter Notebooks and script execution

Working with arrays, dataframes, and series

Data aggregation, filtering, sorting, and reshaping

Time series handling and basic data wrangling techniques

Descriptive statistics and visual distributions

Inferential statistics: hypothesis testing, confidence intervals

Probability theory, Bayes’ theorem, normal and binomial distributions

SQL basics: SELECT, JOIN, GROUP BY, subqueries

Advanced queries and database design

Using Excel for preliminary data exploration and pivot analysis

Data visualization with Matplotlib, Seaborn, and Plotly

Dashboard creation using Tableau and Power BI

Data storytelling and designing reports for business decisions

Supervised learning: linear/logistic regression, decision trees, random forest

Unsupervised learning: clustering (K-means, hierarchical)

Model tuning, cross-validation, evaluation metrics (precision, recall, ROC-AUC)

Neural networks with TensorFlow and Keras

NLP: tokenization, stemming, lemmatization, sentiment analysis

Introduction to RNNs and embeddings for text classification

Model packaging with Flask or Streamlit

REST API creation and integration

Cloud deployment overview and GitHub version control

Choose your domain (finance, e-commerce, healthcare, etc.)

End-to-end pipeline: data cleaning → modeling → dashboard/report

Final project review, mentor feedback, and presentation to hiring panel